Internet media sharing enables users to share media content virtually anywhere at any time using a media capable device with an internet connection. Electronic media libraries may contain very large volumes (e.g., millions of video and/or audio files), in which the task of managing respective volumes presents unique challenges. For example, identifying audio content (e.g., songs, speeches, etc.) from among the volumes of media content is a task often required of media host services in order to recognize copyrighted uploads of music and police appropriate licensing or removal of the copyrighted material.
Audio recognition enables media hosting services to index media files for searching of desired media content. Users can thus quickly identify audio files having particular audio content. For example, a user may seek examples of particular sounds for inclusion in an audio project such as a home movie, audio recording, etc. Audio content such as sounds, audio portions, sound bites, songs, and the like can be tagged with textual labels. However conventional information retrieval of audio content using textual queries can be inaccurate. Moreover, audio content that has undergone transformation such as by being slowed, dubbed, voice overlaid, edited, recorded with a different performer than an original known performer can be difficult to identify by conventional audio recognition systems, and consequently hampering matching of media content for retrieval.